Color digital imaging devices generally utilize an array of color sensors to capture the digital image information. The sensors typically have spectral sensitivities that correspond roughly to the red, green and blue (RGB) portions of the visible spectrum. The sensitivities will vary slightly from one manufacturer to another. Alternatively, sensors with other spectral sensitivities such as cyan, magenta and yellow (CMY), or cyan, magenta, yellow and green have also been used. The exposure values captured by the color sensors are usually converted to an integer value to form quantized color values (intensity values) and stored in memory for later processing. Later processing typically includes color correction, image sharpening and noise removal.
Digital imaging devices are typically designed so that a neutral position or gray patch in the subject area of the image should be encoded with specified code values, i.e., gray balancing is performed on the image. For digital cameras, some type of exposure meter is typically used to determine a lens aperture and exposure time setting that is appropriate for the level of scene illumination. When an electronic flash is used, the flash exposure level is also typically controlled using some form of exposure meter. Other types of digital imaging devices may utilize other forms of exposure control.
Exposure errors can cause the gray patch to come out at code values that are lower or higher than expected. Typical causes of exposure errors are scenes that are dominated by dark or light objects, and scenes where the subject and the background have significantly different exposure levels. For example, photographs will generally have exposure errors when taken with back-lit scenes where the background is brighter than the subject or when taken with flash-lit scenes where the background is at a much larger distance than the subject.
In addition to exposure level errors, color balance errors can also be introduced by variations in the spectral content of the scene illumination. Conventional digital imaging devices are designed so that equal color signals will be generated for neutral scene objects. Color balance errors cause the relative proportions of the color signals for a neutral scene object to deviate from the expected value. For example, if a digital camera is calibrated so that equal red, green, and blue color signals are obtained when a neutral object is photographed with typical daylight illumination, non-equal color signals will generally result when the neutral object is photographed under artificial illumination, e.g., incandescent or florescent lamps.
Scene balance algorithms typically work by analyzing the distribution of overall exposure levels and relative color values in an image to determine the appropriate level of exposure and color balance compensation that is needed. Frequently, these algorithms work by first computing a low-resolution version of the image and then analyzing that image. The low-resolution image is sometimes referred to as a “paxelized” image. The term “paxel” is used to indicate a color value determined by averaging the color values for a group of pixels.
Scene balance algorithms can also be used for digital imaging devices. In this case, the scene balance algorithms must typically be tuned to the color response characteristics of a particular digital imaging device. For example, different digital film scanners or cameras will have different sensor spectral sensitivities. Therefore, the distribution of code values associated with a particular image will be a function of the digital imaging device that is used to capture the image, and different scene balancing algorithms are used accordingly.
The scene balancing algorithm converts the image to a color space that enables it to be properly distinguished between what is illuminant (light source) and what is actual scene content. After the color space transformation is performed, a low resolution version of the image is created and a statistics based approach is used to determine how far away from a specified neutral position (gray patch) the captured image is. Based on the difference between the captured image and the specified neutral difference, color balance gains are created and the subsequently applied to the captured image.
The above method tends to incorrectly discern between illuminant and scene content for imagery that is captured with devices that are a further away from the target or scene to be captured than what would be experienced with scene capture from a standard digital camera. Since the above method was developed primarily for hand-held digital cameras, the method produces sub-standard imagery when capturing remotely-sensed or aerial imagery, e.g., atmospheric effects are not accounted for. In addition, the above method applies a look-up table to prepare the imagery for the application of calculated balance gains. This additional look-up table is not necessary for remotely sensed and aerial imagery, and therefore may yield in inferior results.
In light of the shortcomings of these and other techniques, the need has been felt for a technique to perform in-scene balancing of remotely sensed and aerial multiband images.